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Nanofluid is one of the modern heat transfer fluids that offer the potential to substantially enhance the heat transfer efficiency of conventional fluids. Extensive research has been undertaken to explore its fundamental thermophysical properties specifically viscosity and as well as thermal conductivity. This research emphasizes the significance of hybrid nanofluids and investigates the effect of Brownian motion and thermophoretic phenomena on the characteristics of the Agrawal flow that tends to a stagnation point adjacent to a moving porous disk. The model also accounts for the effects of Smoluchowski temperature and Maxwell velocity slip conditions. Through the utilization of similarity ansatz, the governing partial differential equations are simplified into a class of ordinary differential (similarity) equations. Subsequently, these simplified equations achieved numerical solutions by employing the bvp4c solver, which is specifically designed for fourth-ordered boundary value problems. The study delves into the remarkable impacts of the pertinent embedded parameters on key parameters such as mass transfer rate, heat transfer rate, and shear stress. These effects are brilliantly depicted through a combination of graphs and tables. Graphical analyses disclose the presence of dual solutions within a particular range of the stretching/shrinking parameter. Also, enhancing the solid volume fraction of nanoparticles leads to a notable rise in the shear stress and heat transfer for both solution branches, whereas the mass transfer rate experiences a reduction.

This study to examines the factors that can affect the Exports of Pakistan, by paying particular attention to letter of credit financing of Islamic banks in Pakistan and exchange rate. Sample data of Islamic listed Banks is selected from last twelve years i.e., 2010 to 2022 with 975 observations. Study measure exports performance using exports figures of Pakistan as the proxy for Export performance while external factors namely letter of credit financing of Islamic banks and exchange rate used as an influencing factor. Applying panel analysis, the results provide positive association Pakistan’s Export with Islamic banks letter of credit financing and exchange rate, indicating that easy availability of letter of credit financing and favorable exchange rate can help increase Pakistan’s exports. The study's findings can aid policy managers, particularly those hoping to boost exports and foreign exchange through them, as well as managers seeking to broaden their knowledge of the key elements influencing export performance.

Papillary thyroid carcinoma (PTC) is the most common subtype of thyroid carcinoma. The most effective treatment for PTC is surgical resection, and patients who undergo surgery have good survival outcomes, but some patients have distant metastasis or even multiorgan metastases at the time of initial diagnosis. Distant metastasis is associated with poorer prognosis and a higher mortality rate. Helper T lymphocyte 17 (Th17) cells and regulatory T lymphocytes (Tregs) play different roles in PTC, and the Th17/Treg balance is closely related to the progression of PTC. Th17 cells play anticancer roles, whereas Tregs play cancer-promoting roles. A Th17/Treg imbalance promotes tumor progression and accelerates invasive behaviors such as tumor metastasis. Th17/Treg homeostasis can be regulated by the TGF‐β/IL‐2 and IL‐6 cytokine axes. Immune checkpoint inhibitors contribute to Treg/Th17 cell homeostasis. For PTC, monoclonal antibodies against CTLA-4, PD-1 and PD-L1 inhibit the activation of Tregs, reversing the Th17/Treg cell imbalance and providing a new option for the prevention and treatment of PTC. This article reviews the role of Tregs and Th17 cells in PTC and their potential targets, aiming to provide better treatment options for PTC.

Objective: In patients with coronary artery disease, dual antiplatelet therapy (DAPT) is recommended after percutaneous coronary intervention, but the duration is still debated. This meta-analysis compared short-duration (1 to 3 months) to standard-time (twelve months) double antiplatelet treatment in patients who received coronary intervention with new generation drug eluting Stent. Methodology: To conduct this examination, we methodically looked at PubMed, Cochrane CENTRAL, Embase, and Web of Science databases for randomized controlled trials, evaluating varying durations of double antiplatelet treatment following new generation stents implantation from July to September 2023. Seven randomized controlled trials were included with a total of 22,945 patients. The primary efficacy endpoint was the incidence of Major adverse cardiovascular events, such as cardiac mortality, heart attack, stent coagulation, and target vessel revascularization; while the safety endpoint was the incidence major bleeding. Secondary endpoints were major adverse cardiovascular and cerebro-vascular complications, any bleeding, and net adverse cardiovascular incidence for a year after stent implantation. Results: Short-time DAPT was linked to a significantly less incidence of major bleeding (0.8% vs 1.5%), any bleeding (2.5% vs 4.2%) and NACE (2.5% vs 4.2%) compared to standard duration of DAPT. No significant variation was noticed among the two groups regarding major adverse cardiovascular events (4.1% vs. 4.2%) and acute cardiovascular and cerebrovascular incidents (4.7% vs. 4.8%). Short-duration DAPT in patients with acute coronary syndrome was linked with decreased risk of bleeding and net adverse cardiovascular events. Conclusion: Short-duration DAPT significantly lowers bleeding risk and reduces net clinical adverse events without increasing ischemic risk, making it a reasonable choice for people with new-generation drug eluting stents, particularly those with high bleeding risk or recent surgery.

The use of a hybrid nanofluid, a relatively new invention in the field of nanofluids, results in better heat transmission. In the ongoing investigation, a hybrid nanofluid stagnation point flow involving Fe3O4-CoFe2O4 nanoparticles is utilized. To ensure novelty, the study incorporates reliable thermal properties on a stretching (or shrinking) wedge with variable magnetic fields and heat production, aiming to explore unique features of heat transfer. A set of relevant similarity transformation is utilized to generate ordinary differential equations and further solved numerically to obtain simulation results. The transformed dimensionless equations tackled numerically adopting the bvp5c MATLAB tool. Influence of several pertinent parameters on velocity and thermal distributions is analysed graphically. Surface plot and streamlines is presented for volume fraction and stretching/shrinking effects. It has been shown that magnetic field inclined the flow velocity across the domain due to sheet flow velocity. The wedge term boosted the velocity field, but the temperature distribution is decreased. The internal heating of the energy equation is influenced strongly by the entrenched thermofluidic terms. Computed numerical values are presented as a table for drag force coefficient and rate of heat transfer.

The increasing need for a steady energy supply to enhance efficiency is progressively growing in both residential and manufacturing industries. This demand can be addressed by utilizing advanced technologies like a melting heat generator to produce significant amounts of heat and prevent overheating. Based on the above applications of melting heat, the consequences of melting heat transfer induction on ternary hybrid nanofluid (T-HNF) exposed to solar radiation mechanism in an erratic squeezing flow are considered. The nanoparticles Copper (Cu), Silicon dioxide (SiO2), Zirconium dioxide (ZrO2) are immersed in base fluid Engine oil (EO) resulting in T-HNF (Cu + SiO2 + ZrO2/EO). The model equation also takes into account the entropy generation minimization and Bejan number. Both the spectral collocation technique (SCT) and finite element scheme (FES) are applied to solve the ordinary differential equations (ODEs) through the Mathematica package. Our results reveal that the impact of three-component nanoparticles increases, while the solar radiation parameter raises the energy profile. Also, an increase in the magnetic field deteriorates the velocity distribution. The research has various potential applications, such as in ice and snow melting, solar thermal energy storage, and the food industry.

Abstract Fins are widely used in many industrial applications, including heat exchangers. They benefit from a relatively economical design cost, are lightweight, and are quite miniature. Thus, this study investigates the influence of a wavy fin structure subjected to convective effects with internal heat generation. The thermal distribution, considered a steady condition in one dimension, is described by a unique implementation of a physics-informed neural network (PINN) as part of machine-learning intelligent strategies for analyzing heat transfer in a convective wavy fin. This novel research explores the use of PINNs to examine the effect of the nonlinearity of temperature equation and boundary conditions by altering the hyperparameters of the architecture. The non-linear ordinary differential equation (ODE) involved with heat transfer is reduced into a dimensionless form utilizing the non-dimensional variables to simplify the problem. Furthermore, Runge–Kutta Fehlberg’s fourth–fifth order (RKF-45) approach is implemented to evaluate the simplified equations numerically. To predict the wavy fin's heat transfer properties, an advanced neural network model is created without using a traditional data-driven approach, the ability to solve ODEs explicitly by incorporating a mean squared error-based loss function. The obtained results divulge that an increase in the thermal conductivity variable upsurges the thermal distribution. In contrast, a decrease in temperature profile is caused due to the augmentation in the convective-conductive variable values.

The significant increase in thermal efficiency and the rate of energy exchange used in fuel dynamics and automobile coolants are leading to a better understanding of nanofluids. This computational analysis explores the thermal conductivity performance for radiative cross-flow of a nanofluid across an expanding/constricting sheet with a suction effect as a result of its application. To compute or calculate the magnificent point of nanofluid flow, the entropy, and asymmetrical heat source/sink effects are also elicited. The boundary layers traverse a stream-wise procedure for expanding and contracting sheets. Additionally, the study examines the features of heat transfer and cross-flow of nanofluids using numerical simulations. By employing similarity variables, the basic PDE equations of the current model are transformed into ODEs, and they are subsequently evaluated using the bvp4c method. Therefore, the effects of embedded flow variables on drag force, heat transfer rate, and entropy generation profiles have been framed using parametric research. Multiple solutions are offered for a specific range of the contracting parameter as well as the mass suction parameter. In addition, the heat transfer rate accelerates due to the heat source and decelerates due to the heat sink. The literature that is already published has been compared favorably, and it reveals many commonalities.

This study's primary goal is to examine the mass and heat transfer in the fluid flow between two cylinders while taking the thermophoretic particle deposition impact into account. Only the stretching effect of the inside cylinder under the stationary outside cylinder causes the flow. The governing partial differential equations (PDEs) of the flow dynamics are converted into ordinary differential equations (ODEs) by utilizing similarity transformations. Then, using the shooting approach and the Runge-Kutta Fehlberg fourth-fifth order (RKF-45) method, these simplified equations are numerically solved. Graphical depictions are utilized to analyze the physical behaviour of key factors in detail. The comparison of the published findings with the obtained outcome is given here to check the accuracy and obtained a good agreement with the published results. Results reveal that the gap size strongly influences the momentum, heat and mass transfer fields. Velocity and thermal profiles increase as the curvature parameter upsurges, but the concentration profile declines. It is also observed that when gap width rise, the rate of heat transmission reduces. The findings demonstrate that the mass transportation rate declines as the thermophoretic parameter and thermophoretic coefficient value increase.

This work examines the second law analysis of an electrically conducting reactive third-grade fluid flow embedded with the porous medium in a microchannel with the influence of variable thermal conductivity, activation energy, viscous dissipation, joule heating, and radiative heat flux. A suitable non-dimensional variable is included into the governing equations to transform them into an ensemble of equations that are devoid of dimensions. The acquired equations are then tackled using the Runge Kutta Felhberg 4th and 5th order (RKF-45) approach in conjunction with the shooting methodology. Through comparison with the current results, the numerical results are verified, which provides a good agreement. From the present outcomes, it is established that the entropy generation is supreme for the viscous heating constraint, variable thermal conductivity, Frank Kameneski, heat source ratio parameter and third-grade fluid material constraint. The Bejan number boosts up with larger values of activation energy, and Frank Kameneski constraint and the decreasing nature is noticed for increasing third-grade material parameter, viscous heating parameter. With magnetism, the fluid’s velocity slows down because of a resistive force. A similar impact in the channel on velocity is noticed for larger third-grade fluid, activation energy parameter, and Frank-Kameniski parameters and increasing behavior is noticed for variable thermal conductivity, and permeability parameter. Further, it is cleared that the variable thermal conductivity assumption in the channel plate leads to a significant under prediction of the irreversibility rate.

The present article aims to examine the thermal performance and the sensitivity analysis of a GO−TiO2/water hybrid nanofluid in the presence of different nanoparticle shapes along with heat absorption and thermal radiation effects over a wedge geometry. Analyzing the effects of heat generation and radiation effects is one of the key studies conducted by researchers in various nanofluid flows over some required geometries. However, a combined study of these effects has yet to be studied over a moving wedge, and that combination defines the novelty of the work. Similarity transformations are implemented to the governing equations to obtain the final set of nondimensional equations, which are solved using the bvp4c code in MATLAB. The results obtained were in close agreement with the published results. The Nusselt number decreased with an increase in the heat source parameter Q, and it increased with an increasing Hartree pressure gradient β and thermal radiation parameter Rd. The sensitivity is statistically analyzed for the variations in radiation effect, heat source, and pressure gradient parameters on the Nusselt number. The high values for R2=99.99% and Adj R2=99.96% validate the ANOVA results obtained using a Box–Behnken design (BBD) model in the response surface methodology (RSM) with 14 degrees of freedom. The input parameters Rd and β show positive sensitivity, while Q shows negative sensitivity toward the skin friction. The Nusselt number proves to be most sensitive toward the pressure gradient parameter. TiO2, graphene (Gr), and the derivative forms of graphene, are gaining much importance due to their wide applications in the oil and petroleum industries. Thus, this study contributes to lubrication purposes, emulsion stabilizers, oxalic acid removal, anti-corrosive properties, etc.

Nanofluid plays a crucial role in addressing the heat transmission challenges facing the industries including chemical processing systems, automobile radiators, spacecraft design, concrete heating, solar thermal conversion systems, etc. Consequently, this research is devoted to analyzing the solar radiation mechanism, thermophoresis and Brownian motion under unique conditions, specifically, temperature gradient within liquids with limiting viscosities or plastic dynamic viscosity at zero and infinite shear rate. To increase the model novelty, a model involving two phases of Casson–Carreau fluid conveying tiny particles is developed to analyze the flow of solar radiation mechanism over stationary and moving surfaces. Furthermore, the impacts of heat generation, chemical reaction and activation energy are also taken into account. The dimensionless equations are solved through numerical methods using the Galerkin-weighted residual technique and analytically employing the Homotopy analysis method with the assistance of MATHMATIACA 11.3 software. Our study reveals that the fluid temperature reduces for greater values of Weissenberg number, and Casson parameter. Additionally, the distribution of gyrotactic microorganisms decreased against the bio-convective Schmidt number and Peclet number.

Abstract This research compares the momentum, thermal energy, mass diffusion and entropy generation of two shear thinning nanofluids in an angled micro-channel with mixed convection, nonlinear thermal radiation, temperature jump boundary condition and variable thermal conductivity effects. The $$RKF 45$$ R K F 45 approach was used to solve the Buongiorno nonlinear governing model. The effect of different parameters on the flow, energy, concentration, and entropy generating fields have been graphically illustrated and explained. The hyperbolic tangent nanoliquid has a better velocity than the Williamson nanofluid. The Williamson nanofluid has higher thermal energy and concentration than the hyperbolic tangent nanoliquid in the microchannel. The Grashof number, both thermal and solutal, increases the fluid flow rate throughout the flow system. The energy of the nanoliquid is reduced by the temperature jump condition, while the energy field of the nanoliquid is enhanced by the improving thermal conductivity value. The nanoliquids concentration rises as the Schmitt number rises. The irreversibility rate of the channel system is maximized by the variable thermal conductivity parameter.

Abstract Recently, video transmission is going through many failures because of the limited size of the top-notch technique for storing large volume videos. Thus, video compression (VC) techniques are introduced, which try to eradicate various sorts of redundancies within or betwixt video sequences. However, the VC often falls short to maintain a good quality of compression if motion discontinuities are present in the video frames (VF). To trounce this challenge, this paper proposes an enhanced VC approach via run length-based ASCII Huffman (RLAH) encoding, Kernel-based deep Elman neural network (KDENN), together with modified Kalman filters (MKF) algorithms. Initially, the video is transmuted into frames, and the frame's color space model (CSM) is changed as of RGB to YCbCr. Next, the frames are bifurcated into [8 × 8] blocks, and the significant features are extracted as of every block. On account of these features, the KDENN identifies the motion of every block. Those blocks directly undergo a compression process in case of a single motion. Otherwise, MFK smoothens those blocks in order to eradicate the jitters and undesired movements, and then, it goes through compression. After that, RLAH encoding compresses the VF. Then, on the other side, the RLAH decoding algorithm decomposes the video. The results exhibit that the proposed work renders good quality videos with high PSNR value and also it trounces the prevailing compression techniques concerning compression ratio (CR).

Abstract Early detection of human disease is associated with improved clinical outcomes. However, many diseases are often detected at an advanced, symptomatic stage where patients are past efficacious treatment periods and can result in less favorable outcomes. Therefore, methods that can accurately detect human disease at a presymptomatic stage are urgently needed. Here, we introduce “frequentmers”; short sequences that are specific and recurrently observed in either patient or healthy control samples, but not in both. We showcase the utility of frequentmers for the detection of liver cirrhosis using metagenomic Next Generation Sequencing data from stool samples of patients and controls. We develop classification models for the detection of liver cirrhosis and achieve an AUC score of 0.91 using ten-fold cross-validation. A small subset of 200 frequentmers can achieve comparable results in detecting liver cirrhosis. Finally, we identify the microbial organisms in liver cirrhosis samples, which are associated with the most predictive frequentmer biomarkers.

Studying the combination of convection and chemical processes in blood flow can have significant applications like understanding physiological processes, drug delivery, biomedical devices, and cardiovascular diseases, and implications for various fields can lead to developing new treatments, devices, and models. This research paper investigates the combined effect of convection, heterogeneous-homogeneous chemical processes, and shear rate on the flow behavior of a ternary hybrid Carreau bio-nanofluid passing through a stenosed artery. The ternary hybrid Carreau bio-nanofluid consists of three different types of nanoparticles dispersed in a Carreau fluid model, miming the non-Newtonian behavior of blood. This assumed study generates a system of PDEs that are processed with similarity transformation and converted into ODEs. Furthermore, these ODEs are solved with bvp4c. The results show that the convection, heterogeneous-homogeneous chemical processes, and shear rate significantly impact the bio-nano fluid’s flow behavior and the stenosed artery’s heat transfer characteristics.

The consequence of thermal performance and mass distribution of endothermic/exothermic chemical reaction and pollutant concentration on the nanoliquid stream via cylinder/plate in the presence of permeable media is explored in the present study. The advancement of efficient waste disposal and pollution prevention techniques might result from studies on the fluid flow and dispersion of contaminants in cylinders and plates. Further, TiO2 nanoparticle offers improved thermal conductivity, helps in wide range of technological and industrial applications. The governing partial differential equations (PDEs) of the fluid problem are modeled and converted to ordinary differential equations (ODEs) utilizing similarity variables. The resultant ODEs are numerically solved using Runge Kutta Fehlberg’s fourth-fifth order (RKF-45) scheme. The influence of various non-dimensional parameters on the velocity, thermal, and concentration profiles are illustrated with a graphical representation. The comparison between cylinder and plate geometry is also displayed in graphs. The novel outcomes show that the augmentation of the chemical reaction parameter reduces the thermal profile of the endothermic case and elevates the thermal profile of the exothermic case. Elevating the local pollutant external source parameter leads to a rise in the concentration profile. It is around 10%–12% in Cf, 4%–6% in Nu and 8%–12% Sh observed in cylinder geometry than plate. The mass transfer rate reduces for improved values of solid fraction and activation energy. In all the modes, the cylinder geometry performs better than plate geometry.

Background: People living with chronic kidney disease (CKD) face an increased risk of severe outcomes such as hospitalization or death from COVID-19. COVID-19 vaccination is a vital approach to mitigate the risk and severity of infection in patients with CKD. Limited information exists regarding the factors that shape COVID-19 vaccine uptake, including health information-seeking behavior and perceptions, within the CKD population. Objective: The objectives were to describe among CKD patients, (1) health information-seeking behavior on COVID-19, (2) their capacity to comprehend and trust COVID-19 information from different sources, and (3) their perceptions concerning COVID-19 infection and vaccination. Design/Setting: Cross-sectional web-based survey administered in British Columbia and Ontario from February 17, 2023, to April 17, 2023. Participants: Chronic kidney disease G3b-5D patients and kidney transplant recipients (CKD G1T-5T) enrolled in a longitudinal COVID-19 vaccine serology study. Methods and Measurements: The survey consisted of a questionnaire that included demographic and clinical data, perceived susceptibility of contracting COVID-19, the ability to collect, understand, and trust information on COVID-19, as well as perceptions regarding COVID-19 vaccination. Descriptive statistics were used to present the data with values expressed as count (%) and chi square tests were performed with a significance level set at P ≤ .05. A content analysis was performed on one open-ended response regarding respondents’ questions surrounding COVID-19 infection and vaccination. Results: Among the 902 patients who received the survey via email, 201 completed the survey, resulting in a response rate of 22%. The median age was 64 years old (IQR 53-74), 48% were male, 51% were university educated, 32% were on kidney replacement therapies, and 57% had received ≥5 COVID-19 vaccine doses. 65% of respondents reported that they had sought out COVID-19-related information in the last 12 months, with 91% and 84% expressing having understood and trusted the information they received, respectively. Those with a higher number of COVID-19 vaccine doses were associated with having sought out ( P =.017), comprehended ( P < .001), and trusted ( P =. 005) COVID-19-related information. Female sex was associated with expressing more concern about contracting COVID-19 ( P = .011). Most respondents strongly agreed to statements regarding the benefits of COVID-19 vaccination. Respondents’ questions about COVID-19 infection and vaccination centered on 4 major themes: COVID-19 vaccination strategy, vaccine effectiveness, vaccine safety, and the impact of COVID-19 infection and vaccination on kidney health. Limitations: This survey was administered within the Canadian health care context to patients with CKD who had at least 1 COVID-19 vaccine dose. Race/ethnicity of participants was not captured. Conclusions: In this survey of individuals with CKD, COVID-19 information-seeking behavior was high and almost all respondents understood and trusted the information they received. Perceptions toward the COVID-19 vaccine and booster were mostly favorable.

A novel machine-learning model for micro and mini-channel friction factor prediction is presented in this article. In recent years, periodic array offset strip fins in micro and mini channels have gained attention due to their compactness and aid in heat transfer in chemical processing and electronic cooling devices. The research uses fin length-to-height ratios below one, and Reynolds numbers between one and six hundred contain 2765 geometrically dimensioned. The friction factor, the most significant barrier to heat transfer channel use, must be accurately estimated to design efficient systems. The Krylov subspace method is implemented using the finite element method using the FEniCS software. Additionally, three machine learning algorithms, Catboost, XGboost, and Random Forest regressors, are implemented to predict the friction factor for periodic steady flow through channels with offset strip fin arrays, and the corresponding prediction performance is analysed. A stacking ensemble model is proposed to enhance the precision of friction factor forecasts. The results demonstrate that the proposed method outperforms empirical correlations in predicting friction factor values for specific performance evaluation metrics with an absolute error of 0.403%, indicating that the model accurately represents the complexity of the data.

This paper investigates the impact of homogeneous-heterogeneous chemical reactions on the flow between the coaxial cylinders with heat generation/absorption. From an engineering perspective, in energy absorber design for the shrinking and expanding of a circular metal tube in the production of extruding materials by stretching cylinders designing with great care is necessary to regulate skin friction and heat transfer rate. Studying processes in confined geometries enhances the basic knowledge of chemical kinetics and fluid dynamics. Researchers may increase the chemical processes efficiency/heat transfer activities by designing systems with an optimized flow and analysing the effects of reactions on flow. Both cost reductions and higher-quality products may result from this optimization. This research may yield insights with far-reaching implications across multiple disciplines. The modelled equations are transformed into ordinary differential equations by employing apt similarity transformations and obtained equations are solved using the collocation method with Probabilists’ Hermite polynomial. Graphs illustrating the variation of velocity, thermal, and concentration profiles have been plotted using the influence of various parameters. The increase in curvature parameter causes the velocity and thermal profile upsurge. The rise in heat source/sink parameter improves the heat transport. As the heterogeneous and homogeneous parameters upsurge, the concentration profile decreases.

This paper undertakes a numerical exploration into the dynamics of fluid flow and heat transfer within the stagnation region of a mixed convection scenario involving thermally stratified ternary hybrid nanofluid. The study incorporates the impact of a magnetohydrodynamic and velocity slip, while also considering a permeable sheet that can stretch or shrink. The equations governed the flow problem are transformed into similarity equations using a similarity transformation. Then the similarity equations are solved utilizing the built in solver (bvp4c) in MATLAB. This flow problem has two solutions, as expected. Following that, the outcomes of the stability analysis show the viability and physical robustness of the first solution. Additionally, the study identifies magnetic, suction, and volume fraction as parameters capable of delaying turbulence onset in the boundary layer. Moreover, the heat transmission of the ternary hybrid nanofluid is enhanced by an increased volume fraction. It is important to note that the reported results specifically pertain to the combination of alumina, copper, and titania nanoparticles. Different combinations of nanoparticles may exhibits unique properties related to both flow behaviour and heat transmission.

Abstract Access to dependable and environmentally friendly energy sources is critical to a country's economic growth and long-term development. As countries seek greener energy alternatives, the interaction of environmental elements, temperature, and sunlight becomes more critical in utilizing renewable energy sources such as wind and bioenergy. Solar power has received much attention due to extraordinary efficiency advances. under this context, the present work focus on solar radiation and chemical processes in the presence of modified ternary hybrid nanofluids (THNFs) circulating over an exponentially stretched surface in both aiding flow (A-F) and opposing flow (O-F) circumstances. The primary objective of this investigation is to dive into the complicated dynamics of these structures, which are distinguished by complex interactions involving radiation, chemical reactions, and the movement of fluids. We construct reduced ordinary differential equations from the governing equations using suitable similarity transformations, which allows for a more in-depth examination of the liquid's behavior. Numerical simulations using the Runge–Kutta Fehlberg (RKF) approach and shooting techniques are used to understand the underlying difficulties of these reduced equations. The results show that thermal radiation improves heat transmission substantially under O-F circumstances in contrast to A-F conditions. Furthermore, the reaction rate parameter has an exciting connection with concentration levels, with greater rates corresponding to lower concentrations. Furthermore, compared to the O-F scenario, the A-F scenario promotes higher heat transfer in the context of a modified nanofluid. Rising reaction rate and solid fraction volume enhanced mass transfer rate. The rate of thermal distribution in THNFs improves from 0.13 to 20.4% in A-F and 0.16 to 15.06% in O-F case when compared to HNFs. This study has real-world implications in several fields, including developing more efficient solar water heaters, solar thermal generating plants, and energy-saving air conditioners.

Abstract Cooling and heating are two critical processes in the transportation and manufacturing industries. Fluid solutions containing metal nanoparticles have higher thermal conductivity than conventional fluids, allowing for more effective cooling. Thus, the current paper is a comparative exploration of the time-independent buoyancy opposing and heat transfer flow of alumina nanoparticles scattered in water as a regular fluid induced via a vertical cylinder with mutual effect of stagnation-point and radiation. Based on some reasonable assumptions, the model of nonlinear equations is developed and then tackled numerically employing the built-in bvp4c MATLAB solver. The impacts of assorted control parameters on gradients are investigated. The outcomes divulge that the aspect of friction factor and heat transport upsurge by incorporating alumina nanoparticles. The involvement of the radiation parameter shows an increasing tendency in the heat transfer rate, resulting in an enhancement in thermal flow efficacy. In addition, the temperature distribution uplifts due to radiation and curvature parameters. It is discerned that the branch of dual outcomes exists in the opposing flow case. Moreover, for higher values of the nanoparticle volume fraction, the reduced shear stress and the reduced heat transfer rate increased respectively by almost 1.30% and 0.0031% for the solution of the first branch, while nearly 1.24%, and 3.13% for the lower branch solution.

Lithostratigraphic modeling holds a vital role in mineral resource exploration and geological studies. In this study, we introduce a novel approach for automating pseudo-lithostratigraphic modeling in the deep subsurface, leveraging inversed geophysical properties. We propose a three-dimensional convolutional neural network with adaptive moment estimation (3D Adam-CNN) to achieve this objective. Our model employs 3D geophysical properties as input features for training, concurrently reconstructing a 3D geological model of the shallow subsurface for lithostratigraphic labeling purposes. To enhance the accuracy of pseudo-lithostratigraphic modeling during the model training phase, we redesign the 3D CNN framework, fine-tuning its parameters using the Adam optimizer. The Adam optimizer ensures controlled parameter updates with minimal memory overhead, rendering it particularly well-suited for convolutional learning involving huge 3D datasets with multi-dimensional features. To validate our proposed 3D Adam-CNN model, we compare the performance of our approach with 1D and 2D CNN models in the Qingniandian area of Heilongjiang Province, Northeastern China. By cross-matching the model’s predictions with manually modeled shallow subsurface lithostratigraphic distributions, we substantiate its reliability and accuracy. The 3D Adam-CNN model emerges as a robust and effective solution for lithostratigraphic modeling in the deep subsurface, utilizing geophysical properties.

Rotational effects are investigated in Newtonian ferromagnetic liquids with linear stability modified by temperature and magnetic field. When thermorheological and magnetorheological effects are taken into account, the fluid's rheological behaviour becomes more complex. Thermorheological effects deal with viscosity changes in relation to temperature, whereas magnetorheological effects deal with viscosity changes in reaction to an applied magnetic field. Understanding the interplay between these effects and thermal convection sheds light on how connected these processes are. In idealized boundary conditions, the convective thresholds are expressed explicitly using the Galerkin technique. In the case of free-free and rigid upper-free boundaries, the exchange of stability principle is demonstrated, and corresponding results are presented. The oscillatory convection is not a preferable mode of instability for ferromagnetic liquids with Prandtl numbers more than one. In addition, rotational and ferromagnetic parameters are discussed in relation to system instability. Results reveals that an increase in Taylor number has a stabilizing effect on the system. Increasing magnetic buoyancy number, results in destabilizing effects on the system. Ferroconvection is not affected due to the nonlinearity of non-magnetic parameter. The results obtained agree truly with those of limiting cases.

Numerous large graphs may be constructed from smaller ones, and graph operations are important in many graph theory applications. Here, we investigate the double and the strong double graphs as two graph-theoretical procedures. Alkanes, which simply contain hydrogen (H) and carbon (C) molecules and no additional functional groups, are the most basic and simplest hydrocarbons found in organic molecules. Topological indices come in a variety. There are several degree-based topological indices, including the Banhatti, Zagreb, Randi, and Revan indices (RI). In this paper, we compute a generic formula the first, second, and third Revan topological indices on the double graph and strong double graph of alkanes.

Due to its superior thermal conductivity and efficient thermal management, ternary nanofluids play a crucial role in electronic advance cooling systems, solar thermal collectors, managing efficiency of thermal exchangers, targeted drug delivery systems, and various technologies. An essential aspect of understanding complex systems is studying the interplay between fluid movement, heat transport, and chemical processes. Therefore, examining chemical reactions is vital for various industrial applications in environmental areas. Because of these applications, this study examines the impact of endothermic/exothermic chemical reactions on the flow of a ternary nanofluid across a rotating permeable-stretched surface. The governing equations are transformed into the system of ordinary differential equations (ODEs) and numerically tackled with the help of the Runge–Kutta–Fehlberg 4th 5th (RKF45) order scheme. The outcomes of pertinent constraints on their respective profiles are illustrated through graphs. The results show that the thermal profile diminishes for the exothermic case and enhances for the endothermic case in context to the activation parameter. Improvement in solid volume fraction will improve the rate of thermal distribution for both endo and exothermic cases. The rate of thermal distribution increases by about 3.22% from ternary nanofluid to nanofluid, while the rate of mass transfer is about 2.31%. The outcomes will help in chemical manufacturing, renewable energy technologies, material sciences, and designing and optimization of the delivery of drugs.

Alzheimer’s disease is a chronic clinical condition that is predominantly seen in age groups above 60 years. The early detection of the disease through image classification aids in effective diagnosis and suitable treatment. The magnetic resonance imaging (MRI) data on Alzheimer’s disease have been collected from Kaggle which is a freely available data source. These datasets are divided into training and validation sets. The present study focuses on training MRI datasets using TinyNet architecture that suits small-scale image classification problems by overcoming the disadvantages of large convolutional neural networks. The architecture is designed such that convergence time is reduced and overall generalization is improved. Though the number of parameters used in this architecture is lesser than the existing networks, still this network can provide better results. Training MRI datasets achieved an accuracy of 98% with the method used with a 2% error rate and 80% for the validation MRI datasets with a 20% error rate. Furthermore, to validate the model-supporting data collected from Kaggle and other open-source platforms, a comparative analysis is performed to substantiate TinyNet’s applicability and is projected in the discussion section. Transfer learning techniques are employed to infer the differences and to improve the model’s efficiency. Furthermore, experiments are included for fine-tuning attempts at the TinyNet architecture to assess how the nuances in convolutional neural networks have an impact on its performance.

This study investigates the effects of non-Newtonian Reiner–Philippoff fluids on porous media, particularly in the context of steady radiative mixed convection flow and heat transfer near a shrinking plate surface in the presence of magnetohydrodynamics (MHD). The mathematical model is constructed using PDEs and transformed into ODEs via similarity transformations, with numerical solutions obtained using MATLAB’s bvp4c function. The results demonstrate that boundary layer separation occurs slowest for dilatant fluids and fastest for pseudoplastic fluids, with Newtonian fluids exhibiting moderate separation rates. Thermal radiation and media porosity parameters are found to reduce heat transfer by approximately 0.95% and 0.02%, respectively, while accelerating boundary layer separation. Conversely, magnetic effects and suction parameters increase heat transfer by about 0.08% and 4.25%, respectively, enhancing both fluid velocity and temperature. The mixed convection parameter indicates the possibility of dual solutions, with the opposing flow favoring this phenomenon more than the assisting flow. The time-based stability analysis reveals that the first solution is stable, whereas the second solution is unstable. These findings provide significant insights into the behavior and control of Reiner–Philippoff fluids in practical applications involving porous media and magnetic fields.

This study is carried out to scrutinize the Hiemenz flow for ternary hybrid nanofluid flow across a stretching/shrinking sheet. This study aims to inspect the impacts of variations in the stretching/shrinking parameter and the volume fraction of nanoparticles on key aspects of the ternary hybrid nanofluid flow, specifically the skin friction, Nusselt number (which relates to heat transfer), velocity profiles, and the temperature profiles. The flow equations transform into a system of ordinary differential equations (ODEs) using a similarity transformation. Subsequently, the system is numerically solved using the MATLAB software’s 4th-order accuracy boundary value problem solver, known as “bvp4c”. Numeric findings reveal that skin friction values exhibit variations based on the magnitude of the stretching/shrinking parameter. Moreover, in the specific context of the flow problem being studied, the heat conduction efficiency of the hybrid (ternary) nanofluid surpasses that of the hybrid nanofluid. The system yields two distinct solutions within a specific shrinking/stretching parameter interval. Through an examination of the temporal stability of the solutions, it was determined that only one remained stable over an extended period. Remember that these current findings hold solely for the combination of copper, alumina, and titania.

In the growing need for energy and heightened environmental considerations, the effective control and optimization of thermal processes and transferring mass are of utmost importance. Engine oil and water-based nanofluids have emerged as potential solutions for various industrial applications, from energy generation to sophisticated manufacturing. Because of these demands, the current work aims to explore the need and significance of its research field, providing insights into crucial elements of heat and mass transport properties in the presence of hybrid nanofluids. This work investigates the impact of an induced magnetic field, including hybrid nanoparticle circulation across a stretched surface with an endo/exothermic chemical reaction and the concentration of waste discharge effects. The acquired ordinary differential equations (ODEs) were solved using the Runge Kutta Fehlberg 45 technique. The findings show that engine oil leads to effectiveness in heat transfer, while water-based hybrid nanofluid performs better mass transfer. While motor oil works well in an endothermic situation, water-based hybrid nano liquid has a noticeable effect on heat transfer over the activation energy component in an exothermic chemical reaction process. Further, water-based nanofluids exhibit lower pollutant levels than engine oil when exposed to local pollutant external source parameter. These results provide essential guidance for choosing the best nanofluid for a given engineering problem, leading to greater effectiveness and productivity in various applications, including advanced cooling systems, chemical manufacturing, pharmaceuticals, waste treatment, and pollutant dispersion control.

In the current work, in the presence of a heat source and temperature gradients, the onset of triple-diffusive convective stability is studied for a fluid, and a fluid-saturated porous layer confined vertically by adiabatic limits for the Darcy model is thoroughly analyzed. With consistent heat sources in both layers, this composite layer is subjected to three temperature profiles with Marangoni effects. The fluid-saturated porous region's lower boundary is a rigid surface, while the fluid region's upper boundary is a free surface. For the system of ordinary differential equations, the thermal surface-tension-driven (Marangoni) number, which also happens to be the Eigenvalue, is solved in closed form. The three different temperature profiles are investigated, the thermal surface-tension-driven (Marangoni) numbers are calculated analytically, and the effects of the heat source/sink are studied in terms of corrected internal Rayleigh numbers. Graphs are used to show how different parameters have an impact on the onset of triple-diffusive convection. The study's parameters have a greater influence on porous layer dominant composite layer systems than on fluid layer dominant composite layer systems. Finally, porous parameters and corrected internal Rayleigh numbers are stabilize the system, and solute1 Marangoni number and ratio of solute2 diffusivity to thermal diffusivity of fluid are destabilize the system.

Shallow gas reservoirs play a crucial role in the gas hydrate system. However, the factors influencing their distribution and their relationship with the gas hydrate system remain poorly understood. In this study, we utilize three-dimensional seismic data to show the fluid pathways and shallow gas reservoirs within the gas hydrate system in the Qiongdongnan Basin. From the deep to the shallow sections, four types of fluid pathways, including tectonic faults, polygonal faults, gas chimneys, and gas conduits, are accurately identified, indicating the strong spatial interconnection among them. The gas pipes are consistently found above the gas chimneys, which act as concentrated pathways for thermogenic gases from the deep sections to the shallow sections. Importantly, the distribution of the gas chimneys closely corresponds to the distribution of the Bottom Simulating Reflector (BSR) in the gas hydrate system. The distribution of the shallow gas reservoirs is significantly influenced by these fluid pathways, with four reservoirs located above tectonic faults and polygonal faults, while one reservoir is situated above a gas chimney. Furthermore, all four shallow gas reservoirs are situated below the BSR, and their distribution range exhibits minimal to no overlap with the distribution of the BSR. Our findings contribute to a better understanding of shallow gas reservoirs and the gas hydrate system, providing valuable insights for their future commercial development.

This article explores heat transfer characteristics of magnetohydrodynamics water-base silver (Ag) and iron oxide (Fe 3 O 4 ) hybrid nanomaterials flow in a Darcy-Forchheimer porous medium induced by a stretching/shrinking surface with impacts of heat sink/source. Moreover, thermal radiation effects and the slip boundary conditions are also incorporated in the given problem. Governing partial differential equations (PDEs) are first altered into the ordinary differential equations (ODEs) using suitable similarity transformations. These achieved ODEs are solved by the well-known shooting technique in Maple software to get the required numerical solutions for the variation in different physical parameters. Here, the numerical findings show duality in solutions in case of stretching/shrinking parameter over different ranges of the comprised distinguished parameters. In this regard, the stability analysis is done and the first solution is found stable and physically acceptable, while the second one unstable and physically infeasible. Besides, the skin friction increases for the case of shrinking but it decreases for case of stretching parameter due to the greater impacts of the mass transfer parameter while the heat transfer phenomenon upsurges for the case of shrinking parameter. Moreover, the skin friction, and the heat transfer rise with variation of the suction parameters when the quantity of solid nanoparticles volume fraction is increased.

The development of a better extremely high-efficiency coolant classified as nanofluid for numerous engineering and industrial technologies has been made possible by recent advancements in nanotechnology. In this work, we investigate the impression of an irregular heat generation or heat absorption on the improvement of heat transfer of Williamson hybrid nanoparticles composed of water-based Ag and MgO over a porous surface that is shrinking and stretching. The assisting and opposing flows are also provoked. The non-linear model based on differential equations is derived and numerically handled via a bvp4c process based on some reasonable assumptions. In an appropriate region of mixed convection, mass transpiration velocity, and shrinking surface characteristics, two dissimilar branch outcomes are discovered with the change of the influential parameters. In addition, the analysis of the temporal stability to moderate disruptions is executed on these multiple solutions. It is also discovered that whereas the lower solution is unstable with negative lowest eigenvalues, the upper solution is stable and essentially realistic. In addition, the friction factor and the rate of heat transfer rose by nearly 0.129% and 0.039% for the upper branch solution for superior nanoparticle volume fraction, respectively, and decreases by nearly 0.101% and 0.044% for the lower branch solution. Moreover, the outlines of temperature escalates due to the heat source and decelerates due to the heat sink. Finally, the present fallouts are assessed with the prior findings in a specific case to demonstrate the correctness of the existing technique. This study has a wide range of intriguing applications like heating and cooling systems, geothermal energy plants, aerodynamics, and the manufacture of gate disc valves, etc.

Significance: Bio-nanofluids have achieved rapid attention due to their potential and vital role in various fields like biotechnology and energy, as well as in medicine such as in drug delivery, imaging, providing scaffolds for tissue engineering, and providing suitable environments for cell growth, as well as being used as coolants in various energy systems, wastewater treatment, and delivery of nutrients to plants.Objective: The present study proposes a novel mathematical model for the ternary hybrid cross bio-nanofluid model to analyse the behaviour of blood that passes through a stenosed artery under the influence of an inclined magnetic field. The model considers the effect of expanding/contracting cylinder, infinite shear rate viscosity, and bio-nanofluids.Methodology: The considered model of the problem is bounded in the form of governing equations such as PDEs. These PDEs are transformed into ODEs with the help of similarity transformations and then solved numerically with the help of the bvp4c method.Findings: The results show that the flow rate and velocity decrease as the inclination angle of the magnetic field increases. Additionally, research has found that the presence of nanoparticles in the bio-nanofluid has a significant impact on the velocity and flow rate. Therefore, the flow rate decreases, in general, as the stenosis becomes more severe.Advantages of the study: The results obtained from this study may provide insights into the behaviour of blood flow in stenosed arteries and may be useful in the design of medical devices and therapies for the treatment of cardiovascular diseases.

The limited availability of non-renewable energy resources, the need to protect ecosystems, and financial considerations create a powerful driving force for studying renewable energy and improving thermal energy systems. The utilization of solar radiation and nanofluids containing polyvinyl alcohol–water-based fluids with copper nanoparticles offers an opportunity to improve the efficiency of sustainable solar heating systems. Owing to its usage, this research examines the electromagnetohydrodynamic and thermal transfer of Jeffrey nanofluid flow over a stretchable surface by employing the influence of gyrotactic microorganisms on this flow. Additionally, the current research focused on creating an advanced numerical model that accurately exemplifies the flow and thermal properties of a parabolic trough solar collector (PTSC) installed on a solar plate to generate a continuous energy source. The unique aspect of our research lies in the integrated approach, combining EMHD, nanofluid flow, and stretchable surface technology to investigate the thermal performance of the coating. This innovative combination opens up new possibilities for efficient thermal management in solar energy applications. The effectiveness of thermal transport in PTSC is evaluated by investigating several factors such as the electric field parameter, solar radiation, exponential heat source, bioconvection Rayleigh, and diffusion parameter. This research utilizes invariant transformations to simplify partial differential equations into ordinary differential equations. These equations are then solved using the wavelets and the Chebyshev wavelets scheme (CWS) with the help of MATHEMATICA 11.3 software. The research outcomes revealed that an increase in the solar thermal radiation, and electric field parameters leads to a higher temperature distribution in concentrated solar power. Therefore, this research aims to improve industrial performance by increasing the efficiency of thermal power generation systems.

Thermal critical issues commonly occur in advanced electrical devices as a response to excessive heat generation or a loss in efficient surface area for heat exclusion. This issue can be addressed by utilizing the extended surface to improve the heat transfer performance of the devices. Thus, the present analysis is devoted to scrutinizing the non-Fourier unsteady heat transference of a trapezoidal porous fin. Levenberg–Marquardt technique of backpropagation artificial neural network (LMT-BANN) is employed here to analyze the thermal variation in the fin. The developed governing equation is the hyperbolic heat conduction equation (HHCE), which is transformed into a dimensionless partial differential equation (PDE) using dimensionless variables. LMT-BANN is employed on thermal numerical data and is developed to trace numerical approximation of fin problem using a methodology that includes testing, training, and validation. A graphical visualization of the consequences of thermal variables on the temperature field is presented. The notable evidence of this study reveals that as the magnitude of the convection factor increases, thermal dissipation through the fin gradually decreases. Further, the LMT-BANN technique has been determined to be an effective, reliable, and rapidly convergent stochastic computational solver that can be used effectively for examining the thermal model.

The main objective of this research is to conduct a comparative study of the thermal variations in a dovetail and exponential fin, considering fully wet conditions, ternary nanofluid, and internal heat generation in the form of both linear and non-linear functions. Additionally, the influence of a magnetic field as a driving force for heat transfer systems is taken into account. The mathematical modelling involves the use of dimensionless transformations to convert the energy equation into an ordinary differential equation, which is then analytically solved using the Differential transformation method (DTM). The study focuses on exploring the effects of significant thermal parameters such as radiation conduction, wet factor, heat generation, and ambient temperature on the temperature profile. Graphical analysis is employed to investigate the thermal performance. The main findings indicate that ternary nanoliquid exhibits a higher thermal response compared to nano and hybrid nanoliquid. Moreover, the nonlinear forms of internal heat generation and ternary nanofluids demonstrate a higher rate of heat transfer.

Nanofluids are employed in a variety of human endeavors, such as engineering tools in chemical and power engineering, electronics, medicine, and other areas. Thus, this article investigates the wall jet flow (WJF) and heat transfer (HT) by incorporating the Eyring-Powell nanofluid with a significant consequence of erratic heat source/sink and buoyancy. The leading equations are converted by similarity variables and then obtained numerical solutions by the bvp4c technique. The influences of physical influential parameters on the dimensionless velocity and dimensionless temperature distribution profiles are discussed to predict the behavior of the fluid flow and heat transfer. Also, the heat transfer and friction factor were elaborated with the aid of tables for dimensionless emerging parameters. Moreover, the current results are compared with published results in a limiting case to show the accuracy of the present method. Finally, the current study informs us that the relevant parameters have had a considerable impact on the profiles of the boundary layer.

Cyberbullying has emerged as a pervasive issue in the digital age, necessitating advanced techniques for effective detection and mitigation. This research explores the integration of word embeddings, emotional features, and federated learning to address the challenges of centralized data processing and user privacy concerns prevalent in previous methods. Word embeddings capture semantic relationships and contextual information, enabling a more nuanced understanding of text data, while emotional features derived from text extend the analysis to encompass the affective dimension, enhancing cyberbullying identification. Federated learning, a decentralized learning paradigm, offers a compelling solution to centralizing sensitive user data by enabling collaborative model training across distributed devices, preserving privacy while harnessing collective intelligence. In this study, we conduct an in-depth investigation into the fusion of word embeddings, emotional features, and federated learning, complemented by the utilization of BERT, Convolutional Neural Networks (CNN), Deep Neural Networks (DNN), and Long Short-Term Memory (LSTM) models. Hyperparameters and neural architecture are explored to find optimal configurations, leading to the generation of superior results. These techniques are applied in the context of cyberbullying detection, using publicly available multi-platform (social media) cyberbullying datasets. Through extensive experiments and evaluations, our proposed framework demonstrates superior performance and robustness compared to traditional methods. The results illustrate the enhanced ability to identify and combat cyberbullying incidents effectively, contributing to the creation of safer online environments. Particularly, the BERT model consistently outperforms other deep learning models (CNN, DNN, LSTM) in cyberbullying detection while preserving the privacy of local datasets for each social platform through our improved federated learning setup. We have provided Differential Privacy based security analysis for the proposed method to further strengthen the privacy and robustness of the system. By leveraging word embeddings, emotional features, and federated learning, this research opens new avenues in cyberbullying research, paving the way for proactive intervention and support mechanisms. The comprehensive approach presented herein highlights the substantial strengths and advantages of this integrated methodology, setting a foundation for future advancements in cyberbullying detection and mitigation.

The current analysis aims to find the solution to the buoyancy effect on time-dependent flow and heat transfer induced by a hybrid micropolar nanofluid over a permeable shrinking or stretching vertical flat plate. A novel hybrid nanofluid is utilized, which consists of the agglomeration of water (pure fluid) and two dissimilar nanoparticles like silver (Ag) and titanium dioxide (TiO2). Initially, the model is developed in the form of the non-linear partial differential equations (PDEs) with three independent variables, which are transformed to the set of dimensionless ordinary differential equations (ODEs) using the appropriate similarity transformations. These dimensionless ODEs are solved numerically via the bvp4c package in MATLAB software. The consequence of various involved controlling parameters on the velocity, microrotation, friction drag, temperature, and heat transfer characteristics for the upper branch solution (UPBS) and the lower branch solution (LOBS) are thoroughly inspected. In physical engineering quantities of interest, it is deeply observed that for the case of stretching, the solution of the stable (upper) branch is possible for the entire negative and positive selected values of the stretching/shrinking parameter. In contrast, the lower branch solution exists only for negative values of the stretching/shrinking parameter for the shrinking case.

This paper addresses a mixed and free convective Casson nanofluid flowing on an oscillating inclined poured plate with sinusoidal heat transfers and slip boundaries. As base fluid water is supposed and the suspension of nanofluid is formulated with the combination of individual copper $ \left(Cu\right) $, titanium dioxide $ \left(Ti{O}_{2}\right) $ and aluminum oxide $ \left(A{l}_{2}{O}_{3}\right) $ as nanoparticles, the dimensionless governing equations are generalized based on Atangana-Baleanu (AB) and Caputo-Fabrizio (CF) fractional operators for developing a fractional form. Then, for the semi-analytical solution of the momentum and thermal profiles, the Laplace transformation is utilized. To discuss the influences of various pertinent parameters on governing equations, graphical tablecomparison of the Nusselt number and skin friction is also inspected at different times and numerical schemes. As a result, it has been concluded that both the momentum and energy profiles represent the more significant results for the AB-fractional model as related to the CF-fractional model solution. Furthermore, water-based titanium dioxide $ \left(Ti{O}_{2}\right) $ has a more progressive impact on the momentum as well as the thermal fields as compared to copper $ \left(Cu\right) $ and aluminum oxide $ \left(A{l}_{2}{O}_{3}\right) $ nanoparticles. The Casson fluid parameter represents the dual behavior for the momentum profile, initially momentum field decreases due to the Casson parameter but it then reverses its impact and the fluid flow moves more progressively.

This study examines the effects of a porous media and thermal radiation on Casson-based nano liquid movement over a curved extending surface. The governing equations are simplified into a system of ODEs (ordinary differential equations) using the appropriate similarity variables. The numerical outcomes are obtained using the shooting method and Runge-Kutta Fehlbergs fourth-fifth order (RKF-45). An analysis is conducted to discuss the impact of significant nondimensional constraints on the thermal and velocity profiles. The findings show that the rise in curvature constraint will improve the velocity but diminish the temperature. The increased values of the modified Hartmann number raise the velocity, but a reverse trend is seen for increased porosity parameter values. Thermal radiation raises the temperature, while modified Hartmann numbers and the Casson factor lower the velocity but raise the thermal profile. Moreover, the existence of porous and solid fractions minimizes the surface drag force, and radiation and solid fraction components enhance the rate of thermal dispersion. The findings of this research may have potential applications in the design of heat exchangers used in cooling electronic devices like CPUs and GPUs, as well as microscale engines such as microturbines and micro-heat engines.

The effect of heat and mass transfer on mixed convection flow field with porous matrix in a vertical channel has investigated analytically. The analytical solutions of the coupled nonlinear differential equations are obtained for velocity, temperatures and concentrations are showed graphically. The results obtained analytically by using regular perturbation method are considered to be favorable as no such investigations are performed previously. The governing equations have been made smaller than Non-linear ordinary differential equations by means of flow parameters. Investigations are carried out on the flow characteristics for different values of Grashof number, Reynolds number, Brinkman number, heat generation/absorption parameter and porous parameter. It is found that an increases in the Grashof number cause the buoyancy to increase, which in turn causes the fluid flow for heat generation and absorption to increase.

The properties of nanoparticles in the working fluid are affected by many external factors and it further influences the effective properties of the resulting nanofluid. To study the heat transference mechanism in nanofluids, the inclusion of such factors is quite important as it provides the exact illustration of the mechanism. One such factor is the nanoparticle aggregation effect. Authors have studied the titania–ethylene glycol nanofluid (TiO2/EG NF) flow over a wedge with nanoparticle aggregation effect. Through this communication, authors have attempted to make a development on the Falkner-Skan problem. The flow is developed in the presence of the suction/injection effects, mixed convection, thermal radiation, porous medium, and non-uniform heat source/sink. To account for the influence of nanoparticle aggregation, revised forms of the Maxwell and Bruggeman models and the Krieger-Dougherty model are employed to estimate the effective thermal conductivity and viscosity of TiO2/EG NF, respectively. The aforementioned modified models developed for TiO2/EG NF gave a soundly close agreement with the experimental data. The governing equations are numerically solved employing the “bvp4c function in MATLAB”. The effect of the primary relevant parameters on the velocity, temperature, and heat transmission rate is depicted graphically. The heat transmission rate at the surface is higher with aggregated nanoparticles in comparison to its absence. The higher NPs volume fraction and the aggregation effect enhance the effective viscosity, the fluid becomes denser, and as a result, the velocity decreases. The outcomes of this study will be useful in many fields that utilize applications of flow over wedge such as in raw oil extraction, storage of nuclear waste, insulating heat exchangers, etc.

The current study is focused on the flow of micropolar liquid in a saturated permeable medium sandwiched between clear and hybrid nanofluid filled in an inclined channel, with radiation and dissipation effects. Copper and Aluminium oxide nanoparticles is considered along with base (water) fluid. The solution for velocity, micro rotational velocity, and temperature are determined by applying the regular perturbation technique to the dimensionless version of the governing equations. The heat transport rate at the left y=−1 and right y=2 plate is also calculated, as well as shear stress expressed in terms of skin-friction coefficient and Nusselt number. The result obtained for various physical parameters are analyzed through several graphs and tables. Results reveal that an increase in the material parameter of micropolar fluid, the motion of the fluid flow decreases. The heat transport rate is enhanced and the velocity is degraded by the magnetic parameter. The Hybrid nanofluid temperature is greater when compared to clear and binary hybrid nanofluid. This work establishes the mechanisms for heat transport enhancement on micropolar liquid through a porous medium between a clear and hybrid nanofluid in conducting field.

An anisotropic horizontal porous layer saturated with viscoelastic liquids of the Oldroyd-B type is explored to determine how the internal heat source affects thermal convection. As a momentum equation, a modified Darcy–Oldroyd model is used that takes into account the anisotropy of the porous layer. The energy equation is formulated in such a way that the influence of internal heat sources and anisotropy in thermal diffusivity on the stability criterion may be easily identified. The effects of anisotropy, viscoelasticity, and internal heat generation on the onset of thermal convection are investigated using linear stability analysis. It is understood that convection begins via an oscillatory mode instead of a stationary mode because viscous relaxation, thermal diffusions, and internal heat generation mechanisms compete with one another. Both steady and unsteady finite-amplitude convections are studied using nonlinear stability analysis with the truncated Fourier series method. The effect of different governing parameters on the system’s stability and on convective heat transfer is studied. The present investigation has been significantly validated by the recovery of several prior results as special situations. The findings presented in this work are anticipated to have significant implications for a number of real-world applications, including modeling of oil reservoirs, crude oil extraction, crystal growth, the pharmaceutical and medical industries, and the use of geothermal energy, among others.

Abstract Up‐to‐date information on coronavirus disease 2019 (COVID‐19) outcomes and risk factors in haematopoietic cell transplantation (HCT) recipients is required to inform on decisions about cancer treatment and COVID‐19 mitigation strategies. We performed a meta‐analysis to address this knowledge gap. All studies with at least five patients who reported COVID‐19‐related deaths in HCT recipients were included. The primary outcome was COVID‐19‐related death. Secondary outcomes were COVID‐19‐related mechanical ventilation (MV) and intensive care unit (ITU) admission. The cumulative COVID‐19‐related death rate among HCT recipients was 21% (95% confidence interval [CI] 18%–24%), while MV and ITU admission rates were 14% (95% CI 11%–17%) and 18% (95% CI 14%–22%), respectively. Subgroup analysis showed higher death rates in patients who developed COVID‐19 within 12 months of HCT (risk ratio [RR] 1.82, 95% CI 1.09–3.03), within 6 months of receiving immunosuppressant drugs (RR 2.11, 95% CI 1.38–3.20) or in the context of active graft‐versus‐host disease (RR 2.38, 95% CI 1.10–5.16). Our findings support the idea that HCT should remain an integral part of cancer treatment during the COVID‐19 pandemic but also highlight the need to prioritise preventative measures in those patients who are at increased risk of adverse COVID‐19 outcomes.

Heat transfer effect on peristaltic Newtonian flow in an annular region of eccentric cylinders is considered. An approximate solution for temperature and velocity is obtained using perturbation technique. For constant flow rate, the variation of pressure gradient and velocity with respect to several non-dimensional parameters is studied using graphical representation. It is seen in these graphs that velocity, pressure gradient and temperature enhance with raise in eccentricity and amplitude ratio. Heat diffuses with faster rate with depletion in area of cross section eccentric annulus through parameter inner cylinder radius. Also, velocity rises with increase in heat transfer parameters such as Grashof number and heat transfer co-efficient. Thus velocity of peristaltic flow in eccentric annulus enhances rapidly in presence of heat transfer compared to absence of heat transfer. A study of peristaltic flow in concentric annulus in presence of heat transfer is obtained analytically and compared with present study at eccentricity equal to zero, to validate the approximate solution. It is seen that flow rate increases more in case of eccentric annulus compared to concentric in presence of heat transfer. Present study has application in endoscope, which is important to diagnose problems in internal organs. Also, the variation of pressure gradient helps to maintain flow rate which is essential during insertion of catheter into artery.